Automating Google Searches on a Excel file with AI (4 Steps)

To automate Google searches for an Excel file, import your rows into Datablist, configure the AI Research Agent, and map its answers to new columns. Give it a specific research question and ask for the source URL so you can check each answer before exporting the results.

If research notes grow too long for Excel export, check the Excel cell limit and full-text CSV option before trimming evidence you still need.

I recommend starting with a small sample. A person's name alone can match the wrong executive, and a search result snippet may omit the article's publication date. Including the company and a date range makes the task easier to verify.

This guide uses a list of EMEA executives and looks for press mentions from 2025. You can adapt the same workflow to company news, competitor research, or product information. Website access and available evidence vary, so a missing answer needs review rather than a guessed result.

Step 1 – Clarifying the Requirements

Let's talk first about what you'll need to run automated research on your Excel file:

1. An Excel file containing values you want to automate your research on.
2. An AI research assistant that can handle high volume.
3. A prompt that works.

In this guide I'll focus on:

Finding mentions about EMEA executives in press articles from 2025.

To achieve this I'll use the AI Research Agent in Datablist.

📘 What is Datablist?

Datablist is an AI-Powered Spreadsheet allowing you to clean, enrich and manage your lists and automate workflow such as scaling research on excel files.

Step 2 – Importing List of Executives

Once you have your CSV/Excel file, sign up for Datablist.

Import your Excel or CSV file. For this example, prepare a Name column and a Company column. Keep any existing identifier so you can match the researched rows back to your original file.

Here's a list of the EMEA executives that I'll feed to the AI research agent to find press articles about and avoid repetitive research

Click Enrich to start automating your repetitive research.

Select AI and open the AI Agent.

Step 3 – Prompting the AI research Agent

Once you click on the AI agent, you can start writing your prompt to research at scale

Use a prompt that defines both a valid match and a missing result. Here is a version you can adapt to the example:

Select the matching collection properties as variables in Prompt. Replace 2025 with the period you actually want to research. See the prompt-writing guide for more examples.

Next, you can:

1. Name the column/property where your AI research agent will insert the output.
2. Put a description of your output in the second field.

In this example, I named my output property "Automated Research Results" and told it to use one of the pre-defined output formats. (see image below)

The screenshot uses one result column. For the prompt above, add four Expected Outputs named Automated Research Results, Source URL, Publication Date, and Needs Review. Describe each output using the matching definition in the prompt. Separate columns make missing sources and dates easier to filter.

You also have the option to use more advanced settings that allow you to specify:

1. The AI model to run your automated research with.
2. The maximum number of steps the AI research agent can take.

Once you're done with that, click Continue to output configuration.

Step 4 – Configuring the Outputs

You now have two options:

1. Insert new columns (which is what I'll do)
2. Link automated search results to an existing property by clicking on the icon in the middle and choosing one of the columns you want to link to (see picture below)

This is how it looks when you want to link the automated search results to existing columns

Click on the plus icon (+) in the middle to create the columns.

The results you will get from the AI research agent can be separated into three parts:

1. The run status tracks processing in your collection. The export options let you include run statuses when you need them in the downloaded file.
2. The search results contain the outputs you defined, including the evidence fields for this example.
3. The confidence score is the agent's assessment of its result. It is not a measured accuracy score; check the source even when confidence is high.

Click Instant Run to use the AI Research Agent on your Excel items

When processing finishes, review the results. Run time depends on the number of rows and the research needed for each one. The original example's results look like this:

Check the evidence and export your results

Before running the entire file, open a sample of source URLs. Check that each article mentions the right person and company, falls within your date range, and supports the returned sentence. Include common names and missing company values in your sample.

Keep Unknown results separate from processing errors. An unknown answer may need a more precise name, company, or research question. An error may require checking the run status or settings before retrying. Do not overwrite your original inputs while correcting either case.

Once the sample is useful, process the remaining rows and export the collection to CSV or Excel. Keep the source URLs alongside the answers so your team can review them later.

Conclusion

Scaling research is possible if you use an AI research agent that can automate repetitive Google searches at scale and export the search results to an Excel or CSV file.

Frequently Asked Questions

Is it possible to scale research with Excel?

Yes. For this workflow, you import the Excel rows into Datablist, research each row with an AI Agent, then export the results back to Excel. Define the question, output columns, and evidence you need before processing a large file.

Can this export Google Search Console data to Excel?

This workflow researches public web pages for each spreadsheet row. For clicks, impressions, and queries from your own site, export the relevant Google Search Console report. Choose the page and date range in the Performance report, then export the data you want to analyze. You do not need an AI Agent to look up those metrics.

What is an AI research agent?

An AI research agent is a software tool that can automatically search the internet, gather information, and organize data based on specific criteria you provide. It acts like a virtual research assistant that can work with large amounts of data. Datablist.com has one integrated

How can I automate Google searches?

You can automate Google searches using specialized tools and software that integrate with search engines. These tools can perform multiple searches simultaneously and collect data based on your specified parameters.

What's the difference between web scraping and AI research agents?

Web scraping tools simply extract data from websites based on predefined patterns, while AI research agents can understand context, analyze information, and provide relevant results based on natural language instructions.

How can I speed up my market research process?

Market research can be accelerated by using AI research tools that automate data collection, analyzing competitor information, and gathering market insights from multiple sources simultaneously.

What are the best tools for automating online research?

For automating online research, Datablist.com offers a powerful AI research agent that can process high volumes of searches quickly. This tool is specifically designed for automating Google searches at scale and organizing results in a spreadsheet format.